In order to limit the greenhouse effect causing climate change and reduce the needs of the transport sector for petroleum oils, transformation of lignocellulosic biomass is a promising alternative route to produce automotive fuels, chemical intermediates and energy. Gasification and liquefaction of biomass resources are the two main routes that are under investigation to convert biomass into biofuels. In the case of the liquefaction, due to the unstability of the liquefied products, one solution can be to perform a specific hydrotreatment of fast pyrolysis bio-oils with petroleum cuts in existing petroleum refinery system. With this objective, previous studies [Pinheiro et al. (2009) Energy Fuels 23, 1007-1014; Pinheiro et al. (2011) Energy Fuels 25, 804-812] have been carried out to investigate the impact of oxygenated model compounds on a Straight Run Gas Oil (SRGO) hydrotreatment using a CoMo catalyst. The authors have demonstrated that the main inhibiting effects are induced from CO and CO2 produced during hydrodeoxygenation of esters and carboxylic acids.To go further, cotreatment of a fast pyrolysis oil with the same SRGO as used in the previous. studies was investigated in this present work. Firstly the bio-oil was separated into four fractions by membrane fractionation using 400 and 220 Da molecular weight cut-off membranes. The bio-oil and its fractions were analyzed by spectroscopic and chromatographic techniques. Then, one fraction (i.e. fraction enriched in compounds with molecular weight from 220 to 400 Da) was mixed with the SRGO and co-treated. Despite some experimental difficulties mainly due to the emulsion instability, the hydrotreatment was successful. An inhibition has been observed on the hydro treating reactions of the SRGO in presence of the bio-oil fraction. The measurement of the CO/CO2/CH4 molar flowrate at the reactor outlet showed that the inhibition was due to the presence of CO and CO2 coming from HDO rather than to the oxygen compounds themselves.
In the petroleum industry, the oil fractions are usually complex mixtures containing several hundreds up to several millions of different chemical species. For this reason, even the most powerful analytical tools do not allow to separate and to identify all the species that are present. Hence, petroleum fractions are currently characterized either by using average macroscopic descriptors (density, elemental analyses, Nuclear Magnetic Resonance, etc.) or by using separative techniques (distillation, gas or liquid chromatography, mass spectrometry, etc.), which quantify only a limited number of families of molecules however. Reconstruction methods for the petroleum cuts are numerical tools, which allow to evolve towards a molecular detail and which are all based on the following principle: defining simplified but consistent mixtures of chemical compounds from partial analytical data and from expert knowledge of the process under study. Thus, the reconstruction method by entropy maximization, which is proposed in this article, is a recent and powerful technique which allows to determine the molar fractions of a predefined set of chemical compounds by maximizing an entropic criterion and by satisfying the analytical constraints given by the modeler. This approach allows to reduce the number of degrees of freedom from several thousands (corresponding to the molar fractions of the compounds) to several tens (corresponding to the Lagrange parameters associated with the analytical constraints) and to greatly decrease the CPU time required to perform the calculations. This approach has been successfully applied to reconstruct FCC gasolines by precisely predicting the molecular composition of this type of feedstocks from a distillation and an overall PIONA analysis (Paraffins, Isoparaffins, Olefins, Naphthenes and Aromatics). The extension to other naphthas (Straight Run naphthas, Coker naphthas, hydrotreated naphthas, etc.) is straightforward.
A potential valorization pathway for liquids obtained from lignocellulosic biomass could be their cohydrotreatment with petroleum cuts to produce transportation fuels. Thus, under hydrotreating conditions, biomass compounds are converted through HDO and decarbylation/decarboxylation reactions, leading to the production of CO, CO2, and water. Therefore, it seems essential to consider the impact of COx on the performance of an HDT catalyst in the conversion of a straight run gas oil (SRGO), working under industrial conditions. The conversion of the SRGO was performed at 330 °C, LHSV = 1 h−1, and 5 MPa on a commercial CoMo/Al2O3 sulfided catalyst in the presence of various concentrations of COx (0.0 < molar flow of CO or CO2 < 13.4 mmol/h). The introduction of COx inhibits the HDS and HDN reactions and, to a lesser extent, the hydrogenation of aromatics. Water gas shift and methanation reactions compete with HDT reactions, methane being the major product, and WGS equilibria govern the distribution of the remaining unconverted COx. The formed water is not responsible for the inhibition. From our experiments, it is clear that the inhibition previously observed in the coprocessing of esters or acids (propanoic acid and ethyldecanoate) can be attributed to the COx formed during the reaction.
A mechanistic model of enzymatic hydrolysis taking into account the morphology of the cellulosic particles and its evolution with time was developed. The individual behavior of the main enzymes involved in the reaction (cellobiohydrolases, endoglucanases, and β-glucosidases), as well as synergy effects, were also included. A large panel of experimental tests was done to fit and validate the model. This database included different enzymes mixtures and operating conditions and allowed to determine and compare with accuracy the adsorption and kinetic parameters of the different enzymes. Model predictions on short hydrolysis times were very satisfactory. On longer times, a deactivation constant was added to represent the hydrolysis slowdown. The model also allowed to predict the impact of enzymes ratios and initial substrate parameters (chain length distribution, polymerization degree) on hydrolysis, and to follow the evolution of these parameters with time. This model revealed general trends on the impact of cellulose morphology on hydrolysis. It is a useful tool to better understand the mechanisms involved in enzymatic hydrolysis of cellulose and to determine optimal cellulolytic cocktails for process design.
Understanding the reaction mechanisms involved in the enzymatic hydrolysis of cellulose is important because it is kinetically the most limiting step of the bioethanol production process. The present work focuses on the enzymatic deactivation at the air-liquid interface, which is one of the aspects contributing to this global deactivation. This phenomenon has already been experimentally proven, but this is the first time that a model has been proposed to describe it. Experiments were performed by incubating Celluclast cocktail solutions on an orbital stirring system at different enzyme concentrations and different surface-to-volume ratios. A 5-day follow-up was carried out by measuring the global FPase activity of cellulases for each condition tested. The activity loss was proven to depend on both the air-liquid surface area and the enzyme concentration. Both observations suggest that the loss of activity takes place at the air-liquid surface, the total amount of enzymes varying with volume or enzyme concentration. Furthermore, tests performed using five individual enzymes purified from a Trichoderma reesei cocktail showed that the only cellulase that is deactivated at the air-liquid interface is cellobiohydrolase II. From the experimental data collected by varying the initial enzyme concentration and the ratio surface to volume, it was possible to develop, for the first time, a model that describes the loss of activity at the air-liquid interface for this configuration.
A potential valorization pathway for pyrolysis oils from lignocellulosic biomass is their co-hydrotreatment with petroleum cuts to produce transportation fuels. The study of simultaneous hydrodeoxygenation (HDO) and hydrodesulfurization (HDS) reactions is therefore essential before considering such a co-treatment. The influence of different oxygenated compounds on the hydrotreatment of a straight-run gas oil was studied on a CoMo/γ-Al2O3 catalyst and under industrial operating conditions. The selected compounds were 2-propanol, cyclopentanone, anisole, guaiacol, propanoic acid, and ethyldecanoate, which are representative of the oxygenated chemical families present in bio-oils. Reaction schemes of HDO reactions were proposed for each studied oxygenated compound, and their impact on the gas oil HDS, hydrodenitrogenation (HDN), and aromatic ring hydrogenation (HDCA) was determined. Under our operating conditions, 2-propanol, cyclopentanone, anisole, and guaiacol were not found to be inhibitors of catalytic performances. On the contrary, propanoic acid and ethyldecanoate had an inhibiting effect on HDS, HDN, and HDCA reactions. This inhibition is attributed to a competition between the HDS reactions and the methanation of CO and CO2 formed during the decomposition of ethers and acids. The impact on HDS conversion of dibenzothiophenic compounds was also studied, showing no differences of the inhibiting effect between these molecules.
In this paper, kinetic modeling techniques for complex chemical processes are reviewed. After a brief historical overview of chemical kinetics, an overview is given of the theoretical background of kinetic modeling of elementary steps and of multistep reactions. Classic lumping techniques are introduced and analyzed. Two examples of lumped kinetic models (atmospheric gasoil hydrotreating and residue hydroprocessing) developed at IFP Energies nouvelles (IFPEN) are presented. The largest part of this review describes advanced kinetic modeling strategies, in which the molecular detail is retained, i.e. the reactions are represented between molecules or even subdivided into elementary steps. To be able to retain this molecular level throughout the kinetic model and the reactor simulations, several hurdles have to be cleared first: (i) the feedstock needs to be described in terms of molecules, (ii) large reaction networks need to be automatically generated, and (iii) a large number of rate equations with their rate parameters need to be derived. For these three obstacles, molecular reconstruction techniques, deterministic or stochastic network generation programs, and single-event micro-kinetics and/or linear free energy relationships have been applied at IFPEN, as illustrated by several examples of kinetic models for industrial refining processes.
Gas oil cuts are extremely complex mixtures of several thousands of different chemical species. Consequently, conventional petroleum analyses do not allow to obtain the molecular detail that is required for the development of robust and predictive kinetic models. Recently, two-dimensional Gas Chromatographic techniques (GC2D) have greatly improved the knowledge in the field of characterization of gas oils. However, they remain R&D tools and are hardly utilized in the refining industry. Hence, the goal of the statistical reconstruction of gas oils is to provide a surrogate for this GC2D analysis. To this aim, the gas oil cuts are characterized by means of matrices of molar fractions of pseudo-compounds, which are classified by chemical family and by carbon atom number. The input analyses are the Fitzgerald mass spectrometry, the sulfur speciation (one-dimensional gas chromatography coupled to a specific sulfur chemiluminescence detector) and the total nitrogen and basic nitrogen contents, and allow to quantify the proportions of all the chemical families present in the matrix. The simulated distillation is also used in order to introduce information on the volatility of the gas oil cut. The reconstruction method proposed in this paper is mainly based on a reference statistical distribution of the number of carbon atoms for the side chains connected to the naphtheno-aromatic cores. For each chemical family, the knowledge of the number of potential side chains and the estimation of the maximum length of these alkyl chains allow to determine the carbon number distribution by adjusting of the reference distribution. After reconstruction, the properties of the resulting molar fractions matrix are very close to the analyses used for the reconstruction. Moreover, the method allows to predict, with a high precision, complementary analyses such as the hydrogen content, the aromatic carbon content and the density at 15 ˚C. Finally, the matrix can be efficiently used to develop kinetic models like those employed at IFP to predict the performances of gas oil hydrotreating units.
